Automation index
How much of a Collections officer’s job can AI already do?
An ageing comes earlier. Collecting without breaking the client or letting the invoice die do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Collections officer
27%
AI can already do 27% of this job.
#155 / 623
View rankingCollections officer
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Ageing, buckets and the call.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Deal, the promissory note and the one who does not answer.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Legal, the formal notice and the one who hides.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Sales, credit and not selling to a debtor.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The default, the insolvency and not dressing the balance.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Collect, and not breaking the client.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- ageing
- collection calls
- promissory notes
- formal notice
- trade credit
- defaults
- debtors
- buckets
Sources for this job· O*NET 43-3011.00· ESCO/ISCO 4214
IS WORK OVER?
Climatologist
27%
#140 / 623
View rankingClimatologist
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Series, homogenise and the gap.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Models, scenarios and the uncertainty.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Report, the headline and not selling the easy one.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Field, the station and the one that moves.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The politician, the figure and not staying quiet.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Attribute, and not selling the headline.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- climate series
- homogenise
- scenarios
- uncertainty
- headlines
- stations
- climate reports
- attribution
Sources for this job· O*NET 19-2021.00· ESCO/ISCO 2112